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This research aims to examine the spatial influence on the presence of orangutans. The study models four significant environmental variables: distance from food trees, distance from rivers, elevation, and slope, using the Maximum Entropy (Maxent) software with 10 replications. The results indicate that the environmental factor with the most substantial impact on the presence of orangutans is the proximity to food trees, contributing 90.9%. On the other hand, rivers, elevation, and slope contribute minimally to the modelling. Rivers are recognized as a determinant for orangutan nest presence, given their role as a vital life source for the forest ecosystem. However, in this modelling, the distance from rivers has limited impact due to the prevalence of numerous small rivers throughout the research area. Elevation and slope play a supportive role with modest influence, attributed to orangutans' arboreal nature. These models identify areas sharing similar environmental variables with locations where orangutans are found, suggesting that conditions matching these variables are suitable for orangutans. The habitat highly suitable for Sumatran orangutans encompasses an area of 17.43 hectares (4.14%).

The conflict between humans and wildlife is a critical concern that can destroy human and natural resources. The greatest contribution to human-wildlife conflicts is the destruction of forests as wildlife habitats, causing wildlife to go to human settlements to find other food resources. Collecting data from community perceptions and behavior is needed as an initial step in mitigating human-wildlife conflict. This study was conducted in villages near the forest of the VI Besitang National Park Management Section, Gunung Leuser National Park, Indonesia. This study aims to determine the relationship between behavior and community perceptions regarding forest environmental services in mitigating human-wildlife conflict. Spearmen correlation analysis is used to see the relationship. The results of Spearman’s correlation test showed that people’s perceptions that conflict could cause economic losses had a positive relationship with people’s behavior in improving forests as wildlife habitats with a value of 0.248 (sig <0.05).

Mangrove forest in Lubuk Kertang Village, West Brandan sub-district has been converted around 20 ha annually (1996–2016) into various non-forest land use. Rehabilitation can be a solution to restore the condition of the ecosystem so that it can resume its ecological and economic functions. This paper discusses the evaluation of mangrove rehabilitation carried out by planting 6000 propagules in December 2015 and 5000 seedlings in May 2016 with Rhizophora apiculata species in abandoned ponds. Monitoring was carried out every 6 months from 2016 to 2022. In the restored area, 11 true mangrove species and 3 associated mangrove species were found. The percentage of plants that survived after seven years was 69.42% for planting using propagules and 86.38% for planting with seedlings. The total biomass carbon stocks stored by 7-year-old plants using propagules was 51.18 Mg ha−1, while the carbon stored by planting using seedlings was 56.79 Mg ha−1. Soil carbon stocks at the planted site with propagules were 506.89 ± 250.74 MgC ha−1, and at the planted site with seedlings were 461.85 ± 102.23 MgC ha−1. The total ecosystem carbon stocks (including aboveground carbon) in the planted site using propagules were 558.07 MgC ha−1, while planting using seedlings were 518.64 MgC ha−1. The dataset and findings on the carbon storage evaluation of mangrove rehabilitation will be useful for blue carbon research community and policymakers in the context of the climate change mitigation strategy for Indonesia.

North Sumatra has abundant natural resources and potential as a tourist destination for the wider community. The COVID-19 pandemic has significantly impacted natural tourism, including in North Sumatra, where several tourist attractions have closed their businesses. This study aims to formulate policy priorities for the impact control and restoration of natural tourism sites in North Sumatra. We analyzed the decline in visitors during the COVID-19 pandemic, the impact of the pandemic on the number of visitors, the types of tourist attraction facilities that suffered the most damage, the influence of facility type on the decline in tourist visits, and the aspects of tourism that decreased the most and should be prioritized for improvement. A descriptive statistical analysis, difference tests, and multiple linear regression analyses were used. We found factors that influenced visitor changes before and during the pandemic, as well as afterwards. Our results show that an important development priority is to control the impact of the COVID-19 pandemic on the decline in tourist attractions. We also propose important recommendations for priority policies aimed at the restoration of facilities in the post-COVID-19 development of natural tourism in North Sumatra.

Tidal floods are one of the threats that occur in coastal areas. The impact is felt for the community, as well as other impacts felt for the surrounding ecosystem, namely the mangrove population, where tidal floods that continue to occur can have a serious impact on the community and mangrove vegetation because they can threaten the sustainability of the mangroves. This research uses GIS to map tidal flood inundation areas and determine their relationship with biophysical factors. Spearman correlation is used to determine the relationship between points in tidal flood areas and biophysical factors such as elevation, slope, distance from rivers and distance from the beach. The research results show that the four variable factors are related to the point of tidal flood inundation. Distance from the river greatly influences the tidal flood point in Medan Belawan District, with a correlation coefficient value of -0.100. This is because rivers act as a medium for the entry of water from the sea without any obstacles to entering the land, so when the river flow reaches its carrying capacity, sea water immediately overflows into residential areas.

Mangrove forests play an important role in coastal areas from an ecological perspective, being able to store large amounts of carbon through sequestration and inhibiting climate change processes by absorbing CO2 in the atmosphere. In recent years, there have been changes in the land cover of converted and degraded mangrove forests which have resulted in the release of carbon and an imbalance in soil structure, which in turn cause a flux of CO2 into the atmosphere. This research was conducted at the Karang Gading and Langkat Timur Laut Wildlife Reserve (KGLTLWR) in North Sumatra, Indonesia. The study focused on six different land covers, namely natural forests, restoration, mixed agriculture, paddy fields, oil palm plantation, and ponds. This study aimed to measure the total carbon stock of mangrove forests that have been converted to other land covers and estimate the level of CO2 flux in the area. A total of three transects and six plots for each land cover were used in this study; for tree biomass, a non-destructive method was used by recording every DBH > 5 cm, and for soil carbon, drilling was carried out, which was divided into five depths in each plot. CO2 flux was measured using an Eosense Eosgp CO2 sensor with the static closed chamber method. The highest carbon stock was found at 308.09 Mg ha−1 in natural forest, while the lowest 3.22 Mg ha−1 was found in mixed agriculture. The highest soil carbon was found at 423.59 MgC ha−1 in natural forest, while the lowest 50.44 MgC ha−1 was found in mixed agriculture dry land. The highest average CO2 flux value of 1362.24 mgCO2 m2 h−1 was found in mangrove restoration and the lowest in ponds was 123.03 mgCO2 m2 h−1. Overall, the research results inform how much carbon stock is lost when converted to other land covers so that it can be used as a reference for policy makers to provide future management of mangrove forests and develop mitigation measurements to reduce carbon emissions.

The mangrove forest in Lubuk Kertang Village has been restored by the community since 2009. However, its existence is now disturbed by illegal logging for mangrove charcoal. This study aims to identify of land cover in disturbed mangrove forest areas in Lubuk Kertang Village, Langkat Regency, using Sentinel-2A satellite imagery. Land cover classification was carried out using the Maximum Likelihood, Random Forest, and Multi Layer Perceptron methods. The results show that the Random Forest method achieved higher accuracy, with an Overall Accuracy of 78.98% and a Kappa Accuracy of 80.83%. The estimated mangrove forest area ranged from 523 ha (Random Forest) to 534 ha (Maximum Likelihood). In contrast, the remaining areas were classified as open areas and water bodies. These findings demonstrate that Sentinel-2A imagery combined with machine learning–based classification is more effective for mapping mangrove forest conditions. The spatial information generated is expected to support sustainable management and conservation efforts of mangrove ecosystems in coastal areas of North Sumatra.

Based on orangutan surveys conducted from South Tapanuli to Jambi during 2000–2001 and published scientifically in 2003, evidence of orangutan presence was recorded through the discovery of nests in the coastal swamp forests of Lumut, Central Tapanuli District, North Sumatra. This finding is significant because the site represents a coastal swamp ecosystem that is geographically separated from the Batang Toru landscape, the primary habitat of the Tapanuli orangutan. The data and information indicate a newly identified lowland habitat for the species and suggest potential connectivity between the Batang Toru and Lumut landscapes. However, the area has undergone substantial changes in forest cover. Using the Random Forest classification method in Google Earth Engine (GEE), this study identified an increase in open areas from 84.69 ha (0.06%) in 2000 to 446.22 ha (0.30%) in 2025. Furthermore, forest fragmentation has resulted in the formation of isolated forest patches, with the average distance between patches expanding from 1–2 km in 2000 to 5–10 km in 2025. This fragmentation has disrupted habitat connectivity, leaving the Tapanuli orangutans in the Lumut coastal swamp increasingly isolated and at high risk of local extinction.

The use of Sentinel-2 satellite images for monitoring mangrove forests is widespread, including for detecting illegal logging. The use of vegetation indices in satellite imagery can quickly monitor changes in land cover that occur in mangrove ecosystems. The purpose of this study is to determine the best threshold to monitor changes in mangrove land cover due to illegal logging using Sentinel-2 satellite imagery in Lubuk Kertang Village, Lalat Regency. The methods used included thresholding analysis on the vegetation index Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Mangrove Index (MI). The determination of the best threshold is based by looking at accuracy indicators and separation indices. Accuracy calculations were carried out using a confusion matrix at 192 observation points in the field. The best thresholding analysis results in this study are achieved by using the average thresholding value of NDVI from the 2018-2024 period, which has the highest accuracy of 84%. The NDVI index has a separation index value of 8.259, which shows the best ability among all the vegetation indices tested.

Mangrove forests play an important role in coastal areas from an ecological perspective, being able to store large amounts of carbon through sequestration and inhibiting climate change processes by absorbing CO[sub.2] in the atmosphere. In recent years, there have been changes in the land cover of converted and degraded mangrove forests which have resulted in the release of carbon and an imbalance in soil structure, which in turn cause a flux of CO[sub.2] into the atmosphere. This research was conducted at the Karang Gading and Langkat Timur Laut Wildlife Reserve (KGLTLWR) in North Sumatra, Indonesia. The study focused on six different land covers, namely natural forests, restoration, mixed agriculture, paddy fields, oil palm plantation, and ponds. This study aimed to measure the total carbon stock of mangrove forests that have been converted to other land covers and estimate the level of CO[sub.2] flux in the area. A total of three transects and six plots for each land cover were used in this study; for tree biomass, a non-destructive method was used by recording every DBH > 5 cm, and for soil carbon, drilling was carried out, which was divided into five depths in each plot. CO[sub.2] flux was measured using an Eosense Eosgp CO[sub.2] sensor with the static closed chamber method. The highest carbon stock was found at 308.09 Mg ha[sup.−1] in natural forest, while the lowest 3.22 Mg ha[sup.−1] was found in mixed agriculture. The highest soil carbon was found at 423.59 MgC ha[sup.−1] in natural forest, while the lowest 50.44 MgC ha[sup.−1] was found in mixed agriculture dry land. The highest average CO[sub.2] flux value of 1362.24 mgCO[sub.2] m[sup.2] h[sup.−1] was found in mangrove restoration and the lowest in ponds was 123.03 mgCO[sub.2] m[sup.2] h[sup.−1]. Overall, the research results inform how much carbon stock is lost when converted to other land covers so that it can be used as a reference for policy makers to provide future management of mangrove forests and develop mitigation measurements to reduce carbon emissions.